PROPOSAL ABSTRACT The objective of the proposed research is to investigate how genetic variation influences weight-related traits during the transition from adolescence to adulthood - a critical risk period for weight gain. Genome wide association studies (GWAS) have identified >70 well-replicated loci influencing weight-related traits, some of which vary by race/ethnicity. Few studies have examined the genetic architecture of these traits during this critical period; the discovered loci are largely common variants that explain only a fraction of the estimated trait heritability. Fine-mapping studies suggest allelic heterogeneity; many causal variants remain to be determined. Recent attention has shifted to coding variants some of which may have larger effect sizes and potential to explain more trait heritability. We build on our successes in R01 HD057194 and capitalize on nationally representative, ethnically diverse, prospective and well-characterized data on 10,581 individuals from the National Longitudinal Study of Adolescent Health (Add Health) to assess the association between weight- related traits and coding variants across a 15-year lifecycle period of dramatic weight gain between adolescence and adulthood. In addition, to make full use of this excellent resource, we combine our data with extant exome data from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium (n>91,000) to further assess associations with adiposity phenotypes, an approach that will be particularly informative and powerful for the discovery of novel coding variants. Further, to fully ensure that we capitalize on the uniqueness of our longitudinal data on adolescent to adult weight gain, we combine our data with two well-characterized, age-matched cohorts with exome data (China Health and Nutrition Survey, CHNS n=1,951; Cebu Longitudinal Health and Nutrition Survey, CLHNS, n=1,691) living under different environmental conditions but experiencing high levels of weight gain analogous to Add Health. Using all three datasets, we will determine the genetic and epidemiological architecture of causal variants; identify functional SNPs and genes; and using advanced and innovative statistical modeling, examine differential genetic effects by age, time, and under varying environmental circumstances to downstream cardiometabolic risk factors (diabetes-, blood pressure-, and inflammatory-related markers). We will test novel hypotheses on tempo and timing of risk as well as address each piece of the complex system linking genetic markers, weight-related outcomes, and cardiometabolic risk factors, in the context of a variety of environmental and behavioral confounders. In sum, these data provide outstanding resources for examining low frequency coding variants associated with weight- related and cardiometabolic traits - a rapidly emerging area of science. Our longitudinal and complex analyses in this understudied age range will provide critical information about risk in the transition from adolescence into adulthood, a period of rapid weight gain when precursors of adult disease are developing. Our work will shed light on the progression of risk to inform efforts to mitigate early development of disease risk.